1. Technical Field
The present disclosure relates to proving support to human decision making, and more particularly to timely support of human decision making based on context information.
2. Discussion of Related Art
A decision support system (DSS) is a computer-based information system that supports human decision-making activities. There are five broad DSS categories including: communications-driven, data-driven, document driven, knowledge-driven and model-driven decision support systems.
A communication-driven DSS supports more than one person working on a shared task and examples include integrated tools like Microsoft's NETMEETING or GROOVE.
A data-driven DSS or data-oriented DSS emphasizes access to and manipulation of a time series of internal company data and, sometimes, external data.
A document-driven DSS manages, retrieves, and manipulates unstructured information in a variety of electronic formats.
A knowledge-driven DSS provides specialized problem-solving expertise stored as facts, rules, procedures, or in similar structures.
A model-driven DSS emphasizes access to and manipulation of a statistical, financial, optimization, or simulation model. Model-driven DSS use data and parameters provided by users to assist decision makers in analyzing a situation. They are not necessarily data-intensive.
The global workforce is undergoing a large transformation. The majority of workers are essentially information processors and decision makers, and the quality and timeliness of their decisions will be heavily affected by the quality and timeliness of the information available to them. Moreover, the growth of information in recent years and the increasing number of situations in which important decisions must be made (e.g., natural disasters) demands advances in decision support. Therefore, there is a growing need for a more tailored, contextualized and holistic view of massive data to support decision making.
Context is the auxiliary information that adds meaning to data. This information can be used to customize data processing pipelines or to augment the delivery of insights. The explicit consideration of context in decision support systems is an acknowledgement of the dynamism of decision-making environments, and the associated importance of reducing the number of assumptions that are made at design time.
While data analytics for decision support has been extensively explored in the past, existing systems have not yet reached the point where they can be integrated seamlessly into the human decision making process. Also, existing evidence-based decision support systems do not incorporate the factor of timeliness and context into their evidence-based insight generation procedure.